The first parameter we considered is whether the gender of the user affects the duration that the user takes¶
In [5]:
gender_catblot()
From the previous graph it's clear that the gender of the user is not related to the duration of the trip, since all of the three columns nearly have the same height.¶
The second parameter we considered is whether the user's type (Either Customer or Subscriber) affected the duration of the trip that user takes¶
In [6]:
user_type_catplot()
From the previous graph it's clear that the type of the user (Either Customer or Subscriber) is not related to the duration of the trip, since the two columns nearly have the same height.¶
In [7]:
user_birth_year_duration_plot()
There appears a teeny tiny (expected) relation betweeen age and duration of the trip since the longer durations are from users of younger age (usually).¶
There is no apparent relation what so ever between user's gender and the duration of the trip.
There is no apparent relation between user's type (Either Customer or Subscriber) and the duration of the trip.
The most durations recorded are nearly in the range of 100 ~ 2000 Seconds by the three genders :)
There appears a teeny tiny (expected) relation betweeen age and duration of the trip since the longer durations are from users of younger age (usually).
Most of the users are born between 1980 and 1990, which means the majority are adults between 31 to 41 years old.